大数据驱动下情报研究知识库及其体系架构设计
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摘要
[目的/意义]数据密集型科研环境给传统的情报研究工作带来很大的冲击,情报研究迫切需要不断存储、组织、管理、计算和分析大规模数据资源的方法作为支撑,并需要利用技术有效地整合所需的各种资源。[方法/过程]分析大数据驱动下情报研究面临的挑战和需求,在现有知识库研究的基础上,结合情报研究的概念、目标和流程,提出情报研究知识库。[结果/结论]界定情报研究知识库的概念和内涵,并提出大数据驱动下的情报研究知识库构建思路和架构设计。
[Purpose/significance] Data intensive research environment has brought great shock to traditional intelligence researches. Intelligence analysis is in desperate need of methods to store,organize,manage,calculate and analyze the large-scale data resources,and technologies to effectively integrate various resources required. [Method/process] This paper analyzes the challenges and demands of intelligence analysis driven by big data. On the basis of the existing knowledge base research,and combining with the concept,goals and processes of intelligence analysis,the paper puts forward the intelligence analysis knowledge base. [Result/conclusion] The paper defines the concept and connotation of intelligence analysis knowledge base,and puts forward the construction idea and architecture design of intelligence analysis knowledge base driven by big data.
[Purpose/significance] Data intensive research environment has brought great shock to traditional intelligence researches. Intelligence analysis is in desperate need of methods to store,organize,manage,calculate and analyze the large-scale data resources,and technologies to effectively integrate various resources required. [Method/process] This paper analyzes the challenges and demands of intelligence analysis driven by big data. On the basis of the existing knowledge base research,and combining with the concept,goals and processes of intelligence analysis,the paper puts forward the intelligence analysis knowledge base. [Result/conclusion] The paper defines the concept and connotation of intelligence analysis knowledge base,and puts forward the construction idea and architecture design of intelligence analysis knowledge base driven by big data.
引文
[1]包昌火,王秀玲,李艳.中国情报研究发展纪实[J].情报理论与实践,2010,33(1):1-3.
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[4]张志强.论科技情报研究新范式[J].情报学报,2012,31(8):788-797.
[5]苏新宁.大数据时代情报学与情报工作的回归[J].情报学报,2017,36(4):331-337.
[6] ROWLEY J. The wisdom hierarchy:representations of the DIKW hierarchy[J]. Journal of Information Science,2007,33(2):163-180.
[7]涂子沛.数据之颠:大数据革命,历史、现实与未来[M].北京:中信出版社,2014.
[8]王立学,冷伏海.简论研究前沿及其文献计量识别方法[J].情报理论与实践,2010,33(3):54-58.
[9]包昌火,谢新洲,申宁.人际网络分析[J].情报学报,2003,22(3):365-374.
[10]章成志,梁勇.基于主题聚类的学科研究热点及其趋势监测方法[J].情报学报,2010,29(2):342-349.
[11]李广建,化柏林.大数据分析与情报分析关系辨析[J].中国图书馆学报,2014(5):14-22.
[12]王新昊.情报研究工作中知识地图和知识库的构建研究[D].南京:南京理工大学,2005.
[13]刘建炜,燕路峰.知识表示方法比较[J].计算机系统应用,2011,20(3):242-246.
[14] CORDON O, HERRERA F, VILLAR P. Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base[J]. Fuzzy Systems IEEE Transactions on,2001,9(4):667-674.
[15] QIAN Y,LIANG J,DANG C. Knowledge structure,knowledge granulation and knowledge distance in a knowledge base[J]. International Journal of Approximate Reasoning,2009,50(1):174-188.
[16] BEZAIRE M J,SOLTESZ I. Quantitative assessment of CA1 local circuits:knowledge base for interneuron-pyramidal cell connectivity[J]. Hippocampus,2013,23(9):751-785.
[17]邱均平,王菲菲.数字文献资源语义化计量本体的提出与构建[J].情报学报,2014(10):1012-1021.
[18] PHYTHIAN M. Intelligence analysis today and tomorrow[J].Security Challenges,2009,5(1):67-83.
[2]凌敏.新形势下情报研究工作及其发展的几个问题[J].冶金信息导刊,1999(4):45-47.
[3]包昌火,刘诗章.我国情报研究工作的回顾与展望[J].情报学报,1996(5):344-349.
[4]张志强.论科技情报研究新范式[J].情报学报,2012,31(8):788-797.
[5]苏新宁.大数据时代情报学与情报工作的回归[J].情报学报,2017,36(4):331-337.
[6] ROWLEY J. The wisdom hierarchy:representations of the DIKW hierarchy[J]. Journal of Information Science,2007,33(2):163-180.
[7]涂子沛.数据之颠:大数据革命,历史、现实与未来[M].北京:中信出版社,2014.
[8]王立学,冷伏海.简论研究前沿及其文献计量识别方法[J].情报理论与实践,2010,33(3):54-58.
[9]包昌火,谢新洲,申宁.人际网络分析[J].情报学报,2003,22(3):365-374.
[10]章成志,梁勇.基于主题聚类的学科研究热点及其趋势监测方法[J].情报学报,2010,29(2):342-349.
[11]李广建,化柏林.大数据分析与情报分析关系辨析[J].中国图书馆学报,2014(5):14-22.
[12]王新昊.情报研究工作中知识地图和知识库的构建研究[D].南京:南京理工大学,2005.
[13]刘建炜,燕路峰.知识表示方法比较[J].计算机系统应用,2011,20(3):242-246.
[14] CORDON O, HERRERA F, VILLAR P. Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base[J]. Fuzzy Systems IEEE Transactions on,2001,9(4):667-674.
[15] QIAN Y,LIANG J,DANG C. Knowledge structure,knowledge granulation and knowledge distance in a knowledge base[J]. International Journal of Approximate Reasoning,2009,50(1):174-188.
[16] BEZAIRE M J,SOLTESZ I. Quantitative assessment of CA1 local circuits:knowledge base for interneuron-pyramidal cell connectivity[J]. Hippocampus,2013,23(9):751-785.
[17]邱均平,王菲菲.数字文献资源语义化计量本体的提出与构建[J].情报学报,2014(10):1012-1021.
[18] PHYTHIAN M. Intelligence analysis today and tomorrow[J].Security Challenges,2009,5(1):67-83.